A robust linearly constrained CMA for adaptive blind multiuser detection

A robust blind multiuser receiver, based on a linearly constrained constant modulus algorithm (LCCMA) with multiple constraints and quadratic inequality (QI) constraint on the weight vector norm, is developed in this paper. Quadratic constraints have been a prevalent approach to improve the robustness against mismatch and modeling errors, uncertainties in estimating the data autocovariance matrix, and random perturbations in detector parameters. In this paper, the LCCMA is realized using a fast steepest descent adaptive algorithm based on the partition linear interference canceller (PLIC) structure with multiple constraints and a QI constraint on the weight vector norm. The Lagrange multiplier methodology is exploited to solve the QI constraint problem. Simulations are carried out in a loaded multipath environment with near-far effect to validate the robustness of the proposed detector.